UBC’s Carl L. Hansen, Ph.D., and colleagues claim the resulting nanoliter-scale system not only reduces reagent volumes but results in lower measurement noise, increased sensitivity, and single nucleotide specificity. The researchers describe the system and its use to evaluate miRNA expression and variation at the single cell level in PNAS in a paper titled “High-throughput microfluidic RT-qPCR of single cells.”

Existing methods for measuring transcript levels in single cells include RT-qPCR, single-molecule counting using digital PCR or hybridization probes, and next-generation sequencing, the Canadian team reports. Of these, single-cell RT-qPCR provides a number of advantages in terms of sensitivity, specificity, and dynamic range, but is limited by low throughput, high reagent cost, and difficulties in accurately measuring low abundance transcripts.

While microfluidic-based systems could address a number of issues associated with carrying out RT-qPCR at the single-cell level, they don’t include front-end sample preparation, and require single-cell isolation by FACS or micropipette, followed by off-chip processing and preamplification of the starting template prior to analysis. “The critical step of integrating all steps of single-cell analysis into a robust system capable of performing measurements on large numbers of cells has yet to be reported.”

To address the processing issues, Dr. Hansen’s team has developed a microfluidic system that combines high-throughput single-cell processing and amplification, and is compatible with commercially available assays using "one-pot" RT-qPCR protocols requiring just the sequential addition of reagents into a single reaction vessel. Essentially each cell-processing unit comprises a compound chamber, formed by a cell capture chamber connected sequentially to two larger chambers for RT and qPCR, which allows for the implementation of either heat lysis followed by two-step RT-qPCR or chemical lysis followed by one-step RT-qPCR.

The device features six sample input channels, each divided into 50 compound reaction chambers for a total of 300 RT-qPCR reactions using approximately 20 μL of reagents. Each unit consists of a reagent injection line, a 0.6 nL cell capture chamber with integrated cell traps, a 10 nL reverse transcription (RT) chamber, and a 50 nL PCR chamber. One of the critical design features was the ability to efficiently distribute single cells into each location on the array without causing any cell damage, affecting cell viability or demonstrating bias towards larger or smaller sized cells. To achieve reproducible loading of single cells into each array element, the researchers engineered a hydrodynamic single-cell trap within each capture chamber, and upstream deflectors that essentially focus cells into the central stream where capture is most efficient.

A single-cell suspension is injected into the device, and the cell traps isolate single cells from the fluid stream, enabling initial washing of cells to remove extracellular RNA, cellular debris, or untrapped cells that might cause a background signal or result in low single-cell chamber occupancy. “Importantly, on-chip washing allows for lysis within seconds of washing, thereby minimizing spurious transcriptional responses that may arise from sequential medium exchange and spin steps,” the researchers stress.

After washing, the RT reagent is then injected into the system, reaching each of the chambers in parallel. Following RT the reagent injection line is then flushed through with the PCR reagent to combine with the RT product in the 50 nL qPCR chamber.

The team initially carried out a series of validation experiments to verify the sensitivity, precision, and viability of the system to measure RNA, and then moved on to evaluate the device for measuring miRNA expression in single K562 cells. They found that the system was more precise than matched microliter-volume tube-based experiments on single cells isolated by micropipette. The microfluidic device was capable of accurately measuring the expression of individual miRNAs expressed at levels of just a few copies per cell to 60,000 copies per cell: “a dynamic range of greater than 104 and at single molecule sensitivity,” the authors note. They separately developed an optically multiplexed assay that enabled quantitative measurements of changes in the expression of miR-145 and its target Oct4, at different time points during hESC differentiation.

In a separate set of experiments, the UBC researchers used multiplexed measurements of mRNA single nucleotide variants (SNVs) to assess the genomic heterogeneity of cells taken from a metastatic breast cancer sample. Through these studies they were able to calculate the number of cells that were homozygous or heterozygous for a specific, previously identified variant of the transcription factor SP1.

“We have established the critical element of combining all single-cell-processing steps into an integrated platform,” the authors conclude. “Compared to tube-based single-cell RT-qPCR, microfluidic processing provides improved reproducibility, precision, and sensitivity, all of which may be critical in identifying subtle differences in cell populations. Nanoliter volume also results in a 1,000-fold reduction in reagent consumption, thereby enabling cost-effective analysis of large numbers of single cells. This functionality provides a solid foundation upon which increasingly advanced microfluidic single-cell transcription analysis may be built.”

The team in addition suggests that increasing throughput to over 1,000 measurements on a single device would be straightforward. “We anticipate that more complex fluid routing to distribute cell contents across multiple chambers will allow for the multiplexed measurements of tens of targets across hundreds of cells, and for combining this technology with single-molecule detection by digital PCR.”

Dr. Hansen foresees the technology will have widespread applciations in fields ranging from stem cell research and cancer biology to diagnostics. "This technology, and other approaches like it, could radically change the way we do both basic and applied biomedical research, and would make single-cell analysis a more plausible option for treating patients—allowing clinicians to distinguish various cancers from one another and tailor their treatments accordingly."

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